EMPLOYER PERCEPTION OF THE PERCEIVED USEFULNESS OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT AND SELECTION AT IRINGA MUNICIPAL COUNCIL

Author

Lina T. Majumbi, Haji Ng’elenge


Abstract

 The study examined employers’ perception of the perceived usefulness of Artificial Intelligence (AI) in recruitment and selection at Iringa Municipal Council, Tanzania. The study was guided by one specific objective, which was to examine employers’ perception of the perceived usefulness of AI in recruitment and selection at Iringa Municipal Council. The study employed a qualitative research approach and a case study design. A total of 21 respondents comprising Human Resource Officers, Administrative Officers and Heads of Departments were purposively selected because of their involvement in recruitment and selection activities. Data were collected through semi-structured interviews and analysed using thematic analysis. The findings showed that employers had positive perceptions of the perceived usefulness of AI in recruitment and selection. Respondents perceived AI as useful in improving recruitment efficiency, reducing administrative workload, speeding up applicant screening, supporting candidate matching, improving decision-making and supporting recruitment planning. The findings also showed that AI was perceived to have the potential to simplify recruitment activities and allow employers to handle a large number of applications within a shorter time. The study concludes that employers at Iringa Municipal Council have positive perceptions of the usefulness of AI in recruitment and selection. The study recommends that Iringa Municipal Council should provide staff training and improve ICT infrastructure to support the effective use of AI in future recruitment and selection activities.



Keywords

Artificial Intelligence; perceived usefulness; employer perception; recruitment; selection; human resource management; Iringa Municipal Council.



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References


  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  • Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches(5th ed.). SAGE Publications.
  • Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches(4th ed.). SAGE Publications.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
  • Kallio, H., Pietilä, A.-M., Johnson, M., & Kangasniemi, M. (2016). Systematic methodological review: Developing a framework for a qualitative semi-structured interview guide. Journal of Advanced Nursing, 72(12), 2954–2965. https://doi.org/10.1111/jan.13031
  • Kothari, C. R. (2019). Research methodology: Methods and techniques(4th ed.). New Age International Publishers.
  • Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16, 1–13. https://doi.org/10.1177/1609406917733847
  • Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020). Mitigating bias in algorithmic hiring: Evaluating claims and practices. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency(pp. 469–481). Association for Computing Machinery. https://doi.org/10.1145/3351095.3372828
  • Rogers, E. M. (2003). Diffusion of innovations(5th ed.). Free Press.
  • Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students(8th ed.). Pearson.
  • Strohmeier, S. (2020). Digital human resource management: A conceptual clarification. German Journal of Human Resource Management, 34(3), 345–365. https://doi.org/10.1177/2397002220921131
  • Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910
  • Upadhyay, A. K., & Khandelwal, K. (2018). Applying artificial intelligence: Implications for recruitment. Strategic HR Review, 17(5), 255–258. https://doi.org/10.1108/SHR-07-2018-0051
  • Yin, R. K. (2018). Case study research and applications: Design and methods(6th ed.). SAGE Publications.

 

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